{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T16:27:28Z","timestamp":1774542448599,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685625","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,5]]},"abstract":"<jats:p>Large Language Models (LLMs) have emerged as powerful tools to perform various tasks in the legal domain, ranging from generating summaries to predicting judgments. Despite their immense potential, these models have been proven to learn and exhibit societal biases and make unfair predictions. Hence, it is essential to evaluate these models prior to deployment. In this study, we explore the ability of LLMs to perform Binary Statutory Reasoning in the Indian legal landscape across various societal disparities. We present a novel metric, \u03b2-weighted Legal Safety Score (LSS\u03b2), to evaluate the legal usability of the LLMs. Additionally, we propose a finetuning pipeline, utilising specialised legal datasets, as a potential method to reduce bias. Our proposed pipeline effectively reduces bias in the model, as indicated by improved LSS\u03b2. This highlights the potential of our approach to enhance fairness in LLMs, making them more reliable for legal tasks in socially diverse contexts.<\/jats:p>","DOI":"10.3233\/faia241266","type":"book-chapter","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:01:13Z","timestamp":1733443273000},"source":"Crossref","is-referenced-by-count":3,"title":["InSaAF: Incorporating Safety Through Accuracy and Fairness - Are LLMs Ready for the Indian Legal Domain?"],"prefix":"10.3233","author":[{"given":"Yogesh","family":"Tripathi","sequence":"first","affiliation":[{"name":"Centre for Responsible AI, Indian Institute of Technology Madras, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raghav","family":"Donakanti","sequence":"additional","affiliation":[{"name":"International Institute of Information Technology, Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sahil","family":"Girhepuje","sequence":"additional","affiliation":[{"name":"Centre for Responsible AI, Indian Institute of Technology Madras, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ishan","family":"Kavathekar","sequence":"additional","affiliation":[{"name":"International Institute of Information Technology, Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bhaskara Hanuma","family":"Vedula","sequence":"additional","affiliation":[{"name":"International Institute of Information Technology, Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gokul S.","family":"Krishnan","sequence":"additional","affiliation":[{"name":"Centre for Responsible AI, Indian Institute of Technology Madras, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anmol","family":"Goel","sequence":"additional","affiliation":[{"name":"International Institute of Information Technology, Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shreya","family":"Goyal","sequence":"additional","affiliation":[{"name":"AmexAI Labs, American Express, Bengaluru"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Balaraman","family":"Ravindran","sequence":"additional","affiliation":[{"name":"Centre for Responsible AI, Indian Institute of Technology Madras, India"},{"name":"Wadhwani School of Data Science & AI, Indian Institute of Technology Madras, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ponnurangam","family":"Kumaraguru","sequence":"additional","affiliation":[{"name":"International Institute of Information Technology, Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Legal Knowledge and Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA241266","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:01:13Z","timestamp":1733443273000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA241266"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,5]]},"ISBN":["9781643685625"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia241266","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,5]]}}}